Job Summary:
We are seeking a proactive and innovative Machine Learning Engineer to join our dynamic team. In this role, you will design, develop, and deploy scalable machine learning models that drive key business decisions. You will collaborate closely with data scientists, engineers, and product managers to translate complex datasets into actionable insights and deploy solutions in production environments.
Key Responsibilities:
- Model Development & Deployment:
- Design, build, and optimize end-to-end machine learning pipelines including data ingestion, feature engineering, model training, validation, and deployment.
- Implement best practices for model versioning, testing, and continuous integration/continuous deployment (CI/CD) in production environments.
- Data Analysis & Feature Engineering:
- Work with large datasets to extract, clean, and prepare data for modeling.
- Develop innovative algorithms and robust statistical models to solve complex business challenges.
- Collaboration & Communication:
- Collaborate with cross-functional teams (data science, software engineering, product management) to integrate machine learning solutions into core products.
- Present findings and model insights to technical and non-technical stakeholders.
- Performance Monitoring & Optimization:
- Monitor and evaluate model performance post-deployment; identify, troubleshoot, and resolve production issues.
- Stay current with emerging trends and technologies in machine learning, and propose enhancements to our current systems.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, Mathematics, or a related field.
- At least 3 years of professional experience in machine learning engineering or a similar role.
- Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, sci-kit-learn).
- Solid understanding of statistical methods, data structures, and algorithm design.
- Experience with data processing tools and frameworks (e.g., Pandas, NumPy) and familiarity with SQL.
- Practical experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and containerization (Docker, Kubernetes) is a plus.
Additional Information
- Full-time freelance/consultant with initial contract of 6 months, subject to extension depending on performance
- Must be okay to use your machine (desktop/laptop) and allow our team to install the security tool/app
- Mode of payment: USDT
- Work set-up: remote
- Schedule: Monday - Friday, 10am-7pm (GMT+8)
- Open for expatriates